Sierra vs Decagon (2026)

Sierra

by Sierra

Decagon

by Decagon

Pros

• ✓Co-founded by Bret Taylor, a former Salesforce co-CEO and OpenAI board chair, and Clay Bavor, an 18-year Google veteran who led Google Labs and Lens. Sierra has raised $1B+, most recently at a $15.8B valuation, and reported $200M in ARR in August 2026.
• ✓Outcome-based pricing charges per resolved interaction rather than per seat or conversation, so what a buyer pays tracks resolutions delivered rather than seats purchased.
• ✓Compliance covers FedRAMP High, SOC 2 Type II, ISO 27001, ISO 42001, AIUC-1, HIPAA, GDPR and CCPA, with named audit reports for SOC 2 and HIPAA available under NDA through the trust center.

Limitations

• –Sierra publishes no pricing page, no rate card, no minimum commitment and no per-outcome rate. Every commercial term including the definition of a resolved outcome is negotiated directly.
• –Deployment is sales-led with no self-serve signup. Published customer go-live timelines run from two to ten weeks, and integrations with proprietary systems need custom work through Sierra's integration framework or Agent SDK.
• –Sierra counts 40+ pre-built integrations but does not list them publicly, so buyers confirm coverage in a sales conversation. The MCP route is scoped to ChatGPT Apps, so teams standardizing on another MCP client have no documented endpoint.

Pros

• ✓Agents run on Agent Operating Procedures that support teams write in natural language, with a supervisor model that checks for hallucinations before a response is sent and Watchtower QA reviewing every conversation, so behavior can change without engineering work.
• ✓Outcomes are published against named customers: Chime reports 70% chat and voice resolution, Duolingo an 80% deflection rate, Flashfood a 90%+ deflection rate and ClassPass a 95% cost reduction.
• ✓Zero-data retention is enforced with LLM providers including OpenAI and Anthropic, and the Trust Center lists SOC 2 Type II, ISO 27001:2022, HIPAA and PCI DSS 4.0.1, which suits regulated industries such as fintech and healthcare.

Limitations

• –No rates are published. Decagon offers per-conversation or per-resolution pricing, but both are quoted through sales, so cost cannot be compared with published-rate tools such as Intercom Fin without a scoping call.
• –Deployment is sales-led with an implementation team rather than self-serve, and G2 reviewers report a Time to Implement of 2 months, so it is not a fit for teams that need to launch in days.
• –The third-party review base is small for an enterprise vendor, at 29 G2 reviews, which gives risk-averse buyers less peer validation than larger support platforms offer.